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Found 4,450 Skills
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b
Build voice AI agents with LiveKit Cloud and the Agents SDK. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI", "implement handoffs", "structure agent workflows", or is working with LiveKit Agents SDK. Provides opinionated guidance for the recommended path: LiveKit Cloud + LiveKit Inference. REQUIRES writing tests for all implementations.
Core rules for bkit plugin. PDCA methodology, level detection, agent auto-triggering, and code quality standards. These rules are automatically applied to ensure consistent AI-native development. Use proactively when user requests feature development, code changes, or implementation tasks. Triggers: bkit, PDCA, develop, implement, feature, bug, code, design, document, 개발, 기능, 버그, 코드, 설계, 문서, 開発, 機能, バグ, 开发, 功能, 代码, desarrollar, función, error, código, diseño, documento, développer, fonctionnalité, bogue, code, conception, document, entwickeln, Funktion, Fehler, Code, Design, Dokument, sviluppare, funzionalità, bug, codice, design, documento Do NOT use for: documentation-only tasks, research, or exploration without code changes.
Teaches AI agents to recognize and avoid security threats during normal activity. Covers phishing detection, credential protection, domain verification, and social engineering defense. Use when building agents that access email, credential vaults, web browsers, or sensitive data.
Fetch markdown snapshots from websites into the local repository using Cloudflare Markdown for Agents, with robust HTML-to-markdown fallback.
Use when implementing RL algorithms, training agents with rewards, or aligning LLMs with human feedback - covers policy gradients, PPO, Q-learning, RLHF, and GRPOUse when ", " mentioned.
Multi-Agent Architecture Design and Intelligent Spawn System. Use this skill when you need to design a multi-agent system, configure specialized agents, implement intelligent task distribution, or optimize concurrent processing capabilities.
Community incident reporting for AI agents. Contribute to collective security by reporting threats.
Web UI testing and browser automation with Vercel agent-browser. Use when tasks require opening pages, interacting with forms, validating UI flows, taking screenshots, extracting page data, or running repeatable browser-based checks locally or in CI.
Configure which review agents run for your project. Auto-detects stack and writes compound-engineering.local.md.
Expert blueprint for GDSkills skill discovery and indexing system. Enables AI agents to find relevant skills by topic/keyword. Use when building skill libraries OR implementing search functionality. Keywords skill discovery, indexing, search, metadata, skill registry.
Use when compressing agent context, implementing conversation summarization, reducing token usage in long sessions, or asking about "context compression", "conversation history", "token optimization", "context limits", "summarization strategies"